There is still the problem of rare pathologies with small available datasets, and the results indicate that it is necessary to finetune on them to make reasonable predictions.
Maybe the idea of federated and distributed learning as applied by Ken et al.[1]} could overcome the problem of rare datasets and pathologies by sharing the network weights across distributed institutions.
